Iterative Clipping Noise Recovery of OFDM Signals Based on Compressed Sensing

Abstract

The simple method of clipping is widely used to reduce the peak-to-average power ratio of orthogonal frequency division multiplexing (OFDM) signal prior to passing it through the high power amplifier (HPA). However, clipping is a nonlinear process that causes both in-band and out-of-band distortions. Filtering the clipped OFDM signal can eliminate the out-of-band distortion but it can lead to peak regrowth. Therefore, iterative clipping and filtering have been used to both remove the out-of-band interference and suppress the regrowth of the peak power. However, the iterative process will degrade the bit error rate performance further. In this paper, we proposed a semi analytic scheme based on compressed sensing to reconstruct the iterative clipping noise. Moreover, the proposed scheme is also applicable for reconstructing the total nonlinear distortion of a system so that the OFDM signal passes both the clipper and HPA. Simulation results show that the proposed scheme performs well and the nonlinear distortion can be recovered effectively.

Existing System

Genetic algorithm.

Proposed System

In this paper, a modified scheme with the noise enhancement factor using CS is proposed to reconstruct the total nonlinear distortion of the system which involves iterative clipping and filtering and SSPA. To make use of the CS method, the noise enhancement factor in the model of ICF is determined by simulation. However, simulation results have verified its validity and uniqueness. Compared with the performance of conventional ICF, the proposed scheme using CS performs well by exploiting the noise enhancement factor to quantify the total nonlinear distortion and so the nonlinear distortion could be recovered effectively.

Architecture

BLOCK DIAGRAM

ICF noise recovery scheme